The Goodness-of-Fit Test for Four - Parameter Kappa Distribution
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Abstract
The objective of this study was to investigate the comparison of the power of test statistic by a goodness of fit test for Four Parameter Kappa Distribution. The test with 6 types of goodness-of-fit-test include Kolmogorov–Smirnov ( ), Anderson-Darling (
), Modified Anderson-Darling (B2 ), Cramer-von Mises(
), Zhang Anderson-Darling (
) and Zhang Cramer von-Mises (
). For estimating function, the power of test statistics with two distributions was symmetry distribution and asymmetric distribution. However, the researchers were applying Monte-Carlo method for simulation with 10,000 replicated. The results show that, the most powerful test statistics are
, and
for symmetric distribution, and the
is the most powerful test for asymmetric distribution.
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References
Abidin, N.Z., Adam, M. and Midi, H. 2012. The Goodness-of-fit Test for Gumbel Distribution : A Comparative Study. MATEMATIKA 28(1): 35-48.
Bradley, J.V. 1978. Robustness. British Journal of Mathematical and Statistical Psychology 31(2): 144-152.
Coles, S. 2001. An Introduction to Statistical Modeling of Extremes Values. Springer, London.
Hosking, J.R. 1994. The four-parameter kappa distribution. IBM Journal of Research and Development 38(3): 251-258.
Laio, F. 2004. Cramer-von Mises and Anderson-Darling goodness of fit tests for extreme value distributions with unknown parameters. Water Resources Research 40(1): 1-10.
Liao, M. and Shimokawa, T. 1999. A new goodness-of-fit test for type-1 extreme value and 2-parameter Weibull distributions with estimated parameters. Journal of Statistical Computation and Simulation 64(1): 23-48.
Shabri, A. and Jemain, A.A. 2008. The Anderson-Darling test statistic of the generalized extreme value. Malaysian Journal of Industrial and Applied Mathematics 24(1): 85-97.
Zempléni, A. 2004. Goodness-of-fit Test in Extreme Value Applications. Collaborative Research Center 386: 1-13.
Zhang, J. 2002. Powerful goodness-of-fit tests based on the likelihood ratio. Journal of the Royal Statistical Society 64(2): 281-294.
Zhang, J. and Wu, Y. 2005. Likelihood-ratio tests for normality. Computational Statistics and Data Analysis 49(3): 709-721.